Forthcoming, Economic Development and Cultural Change

Can Institutions Resolve Ethnic Conflict? 1

Abstract: High quality institutions, such as rule of law, bureaucratic quality, freedom from government expropriation, and freedom from government repudiation of contracts, mitigate the adverse economic consequences of ethnic fractionalization identified by Easterly and Levine 1997 and others. In countries with sufficiently good institutions, ethnic diversity does not lower growth or worsen economic policies. High quality institutions also lessen war casualties on national territory and lessen the probability of genocide for a given amount of ethnic fractionalization; however, these forms of violence are not the channel by which ethnic fragmentation and its interaction with institutions affect economic growth. William Easterly

World Bank

1

Some of the results in this paper are based on earlier unpublished work with Ross Levine. Views expressed here are not necessarily those of the World Bank or its member governments.

2

In 88 BC, King Mithriadates VI of Pontus invaded Roman territory in Asia Minor. He encouraged Asian debtors to kill their Roman creditors. Happy to reduce their credit card bills, the Asians massacred 80,000 Romans. 1 Ethnic conflict is a tragic constant of human history. Ethnic conflict is still very much in the news today, from the Balkans to Central Africa to Indonesia to Nigeria. Ethnic conflict has a peaceful political dimension as well as the more publicized violent dimension. Recently, the economics literature has studied the effects of ethnic conflict on economic development. Easterly and Levine [1997] document an adverse effect of ethnolinguistic fractionalization on income, growth, and economic policies. They offer this as an explanation for Africa’s poor growth performance. Alesina, Baqir, and Easterly 1999a find that more ethnically diverse cities and counties in the US spend less on public goods. Goldin and Katz 1999 find lower public support for higher education in states with more religious - ethnic heterogeneity. Goldin and Katz 1997 likewise find lower high school graduation rates in states that had higher religious-ethnic diversity. Miguel 1999 likewise finds lower primary school funding in more ethnically diverse districts in Kenya. Mauro 1995 and La Porta, Lopez de Silanes, Shleifer and Vishny 1998 find that ethnic diversity predicts poor quality of government services. Mauro 1995 and Annett 1999 finds that linguistic or religious diversity leads to greater political instability, which Annett finds in turn leads to higher government consumption. Alesina, Baqir, and Easterly 1999b find a link from ethnic diversity to bloated government payrolls in US cities. Rodrik 1999 noted that ethnically polarized nations react more adversely to external terms of trade shocks. Svensson 1998 finds that more foreign aid proceeds are diverted into corruption

3 in more ethnically diverse places. Knack and Keefer 1997 find that ethnic homogeneity raises “social capital” or “trust,” which in turn is associated with faster growth and higher output per worker. Alesina and La Ferrara 2000 and Zak and Knack 1999 also find that ethnic heterogeneity lowers "trust," using US data and cross-country data, respectively. Alesina and La Ferrara 1999 find that higher ethnic heterogeneity makes participation in social clubs less likely in the US, which is consistent with the idea that there is not much association across groups. Adelman and Morris 1967 also noted that “cultural and ethnic heterogeneity tend to hamper the early stages of nation-building and growth.”2 There is a large political science literature that describes the formation of ethnically based political blocs. Rothchild (1991), one of the leading scholars of ethnic politics, avers that “ethnic and other rivalries” over “distributive goods” are “farreaching”(p. 195). 3 For example, in Zambia, Scarritt (1993) describes how the Nyanja group (15 percent of the population) was in power through 1991 under the undemocratic rule of Kenneth Kaunda. The Bemba group (37 percent of the population) had been discriminated against under Kaunda because he feared they were opposition sympathizers. Food riots against the first IMF agreements in the late 80s took place primarily among the Bemba population. In democratic elections that were finally held in 1991, the Bemba group led the winning coalition, while the party supported by the Nyanja lost. In Nigeria, likewise, the predominant (albeit far from the only) ethnic split has been between the Muslim North and the Christian South. Collier [1995] states flatly: “the Nigerian government is a Northern interest group. This group has never relinquished power since independence.” Ake [1996] concludes that most of Nigeria’s

1999 has called “ethnic capital”). yet over the same period school enrollment shrunk due to tight education funding. the states rely on handouts of oil money from the central government. For example. Although Nigeria is a constitutional federation. religious. 1995. The competition for rents from oil often seems to divert resources away from human capital accumulation (as predicted by Tornell and Lane 1999). The Nigerian dissident writer Wole Soyinka (1996) notes that a governmentappointed commission of inquiry was unable to account for what happened to much of the 1990s government oil windfall. local school finance.4 elites “place their Nigerian identity below that of their local community. public spending in Nigeria during the oil boom in the early 1990s increased by more than 50 percent. He notes "ethnic. The current Prime Minister of Ethiopia. Most recently. 67]. Oil is actually produced in the South. but tensions continue between Northern and Southern groups over issues like the introduction of Islamic law in Northern states. summed up the political economy of Africa in a speech at Harvard." Ethnic groups may act selfishly in their own interest. or ethnic group” [p. and
. because they may receive only spillovers from the human capital or knowledge of those in their own ethnic or neighborhood group (what Borjas 1992. Meles Zenawi. nation. Case and Katz 1991 found there were strong neighborhood effects on economic and social outcomes for Boston inner city youths. Benabou 1993 and Durlauf 1996 suggest that inequality persists through neighborhood externalities. a Southerner has finally become President of Nigeria under democratic elections. It is the centerpiece of our economies (Zenawi 2000). and other sources of diversity are the hall-marks of African societies" and "Rent-seeking in our economies is not a more or less important phenomenon as would be the case in most economies.

5 endogenous segregation between rich and poor. The existence of “ethnic capital” makes for persistent income differentials between ethnic groups. Societies that are ethnically divided are plausibly more prone to "polarization" and "social conflict. p. for example. because ethnic diversity was still significant after controlling for civil war). 4 Ethnic inequality may lead to some poor groups being unable to finance human capital accumulation. Each ethnically-based interest group tries to free ride on inflation stabilization. I. The exclusion of some ethnic groups from enterprise and human capital formation lowers the productive potential of the society that excludes them. 38). (Easterly and Levine 1997 found that this ethnic effect was not proxying for real wars fought along ethnic lines. Although we could capture such policy reforms directly in the growth equation. with such inequality lowering growth. Growth regression with Institutions Political economy explanations of development outcomes usually focus on “society’s polarization and degree of social conflict” (Alesina 1994." The adverse effect of ethnic diversity on growth may stem from the political economy “wars of attrition” (Alesina and Drazen 1991) that take place between ethnic groups. Casella and Rauch 1997 argue that exporters with an ethnic connection to business groups inside the importing country have an advantage over those without such ties. the poverty rate among indigenous people is 81 percent. so ethnic
. hoping that the costs will be borne by the group that initiates the reform. which may exacerbate ethnic tensions. or another costly policy reform. as argued in general for inequality and growth by Galor and Zeira 1993. trade opening. while it is only 18 percent among non-indigenous Mexicans. In Mexico. there are many structural reforms that are hard to measure (such as lowering price distortions or privatization). privatization.

To change the metaphor. and facilitate cooperation for public services would constrain the amount of damage that one ethnic group could do to another. Institutions that give legal protection to minorities. we could measure such public services directly. leading to less total spending on growth-promoting public goods -. Good institutions would thus
.as documented for US cities and counties by Alesina. to keep adding metaphors. Again. Such pro-business rules of the game may prevent ethnic groups from expropriating business owners of a different ethnic group.6 diversity may show up in the growth equation because it represents a bad political economy equilibrium in some unmeasurable policies. grant freedom from repudiation of contracts. in which a country might have a growth-promoting comparative advantage. but many of them are hard to observe directly. Ethnic diversity may then have a direct effect on growth through its effect on unobserved public services. as argued by the literature cited above. Such a bad political economy equilibrium with polarized ethnic groups can literally. and Easterly 1999a. Baqir. guarantee freedom from expropriation." Lower "trust" between diverse ethnic groups make it difficult to form the social networks ("social capital") that promote growth by disseminating advanced technology and economically useful knowledge. ethnic groups may each try to extract rents from the commodity (with a strong incentive to get the rents before the other group does) until commodity producers are discouraged from producing. Rather than protecting a valuable resource like cocoa plantations. "kill the goose that lays the golden egg. Ethnic groups may have difficulty agreeing on the type of public goods. multiple ethnic groups are subject to “the tragedy of the commons” as each ethnic group over-extracts from a common resource like commodity export rents.

" and therefore are more productive at the margin than in homogeneous societies.
. Mauro [1995] and Knack and Keefer [1995] argue that corruption and other institutional factors are correlated with economic growth using data from country risk services for international investors. In a society with ethnic conflict. f2 <0. formal institutions fill the gap left by lower "social capital. formal institutions that protect minorities and establish clear legal rules for business may be more valuable in ethnically divided societies than in homogeneous ones. In ethnically divided societies. These studies argue that the ability to resolve conflicts peacefully and quickly. and to have confidence in the bureaucracy may all influence investment and allocation decisions. Poor institutions in Africa may reinforce the ethnolinguistic fractionalization explanation for Africa’s poor performance. In ethnically homogeneous societies. to conduct business where the rules of the game are clear. and ∂2 (Ethnic conflict)/(∂ Ethnic diversity∂Institutional quality)<0. Institutional quality) where f1 >0. the web of social networks spanning the whole society will spawn informal institutions ("social capital" or "trust") that provide assurance against expropriation or breaking contracts. We can think of an interaction effect between quality of institutions and ethnic diversity that would work something like this: (Ethnic conflict) = f(Ethnic diversity. such institutional shortcomings may be disastrous.7 plausibly make a given amount of ethnic fractionalization less damaging for development. Many studies of Africa cite the hostile institutional environment as a factor explaining Africa’s poor growth performance (see World Bank [1994]). 5 As a corollary.

(b) freedom from expropriation. For example. as do others in the literature. rule of law. the outcomes of institutional arrangements. so I can check my assumption of persistence over time. has a maximum possible value of 10 and potential minimum of 0. Then. I average these across years 1980-1989 in computing the overall institutional quality index.9 and 2. INSTITUTIONS is highly correlated (. This index.8 Good institutions may thus mitigate ethnically-based social conflict that lowers growth.87) with the general institutional ranking of the Business Environment Risk Guide (BERI) for 1980-1989 reported by Knack and Keefer 1995. I prefer to use the ICRG data however. (c) rule of law. I find a correlation of . Rather I am measuring. I find that the ethnic effect in the original Easterly and Levine 1997 growth regressions disappear if institutions are of sufficiently high quality. for example.
. I average Knack and Keefer’s [1995] measures from the International Country Risk Guide of (a)freedom from government repudiation of contracts. as in Barro [1997]. and (d) bureaucratic quality into an overall index of institutional quality. 6 BERI data covers the 1970s and 1980s. INSTITUTIONS. Luxembourg has a institutional index value of 10.7 respectively. while Liberia and the Sudan have values of 2. I use the 1980s value for the 1970s and 1960s under the assumption that institutional quality changes slowly. because they cover more countries and because they were the principal variable in the seminal Knack and Keefer 1995 study. Data are available for many of the years in the 1980s. Note that I am not directly measuring the political and social institutions that might foster.95 between the BERI averages for 19701979 and 1980-1989.

the results indicate that ethnic diversity has a zero marginal effect on economic growth at maximum institutional development (INSTITUTIONS equal to 10). The data still demonstrate that ethnic diversity is negatively associated with long-run growth.88 with Knack and Keefer’s [1995] 1980-1989 index of corruption.33. 7 Indeed. However. Table I’s results imply that sound institutional arrangements mitigate the negative effects of ethnic diversity. where 1 is the most democratic. INSTITUTIONS*ETHNIC to the most complete growth regression of Easterly and Levine 1997. I add the interaction term. These results suggest that it is institutions rather than democracy that contain ethnic conflict. which in turn has a correlation of . This result may be related to that of Collier 1999 that democracy eliminates the adverse effect of ethnolinguistic fractionalization on growth. although some of the policy variables are no longer significant in the small cross-section sample. I test whether democracy is more relevant than institutions by adding a variable ETHNIC*POLRIGHTS. I get similar results (Table I) on the ethnic variable and its interaction with institutions. with the wrong sign and a t-statistic of only . when I control for a measure of intensity of war (war casualties on
. However. Because of concern about possible autocorrelation of the error terms in the pooled data. INSTITUTIONS has a correlation of .8 with Mauro’s [1995] 1980-1983 index of corruption.9 INSTITUTIONS is also highly correlated with corruption. In Table I. where POLRIGHTS is the Gastil index of political rights from 1 to 7. Another possible concern is that ethnic fragmentation and its interaction with good institutions may simply be picking up the presence of violence destructive to growth. I also do the regression as a pure cross-section. This variable is insignificant.

effective “rules of the game. Ministries might be parceled out among the various ethnic leaders. freedom from expropriation. but I do acknowledge the possibility. I explore the effect of institutions on mitigating the adverse effects of ethnic diversity on policy. Institutions. suppose that a multi-ethnic coalition is necessary to constitute a majority in an ethnically diverse country. Likewise. This problem creates difficult identification problems that I cannot resolve in this paper.” and an efficient bureaucracy -. For example. and Policy Choices Next. who seek gains for their own ethnic group at the expense of other ethnic groups. countries may be able to adopt institutional arrangements -. Ethnic Diversity.10 national territory). I find the growth effects of ETHNIC and its interaction with INSTITUTIONS to be unchanged. The result would be a high black market premium.clear property rights. Finally. Clear rules of the game may substantially reduce or eliminate costly rent-seeking behavior associated with ethnic diversity. while genocide itself does not significantly lower growth. while the war variable is itself insignificant. the results on ETHNIC and its interaction with INSTITUTIONS are unchanged. II. The ethnic leader in charge of bank regulation might put controls on interest
. when I control for a dummy variable measuring genocide (to be described below).that mitigate the negative repercussions of diverse interest groups. it may be that ethnically diverse societies with good institutions are those that had less tension between groups to begin with. While ethnic diversity is given exogenously. The ethnic leader in charge of the central bank might set an artificially overvalued exchange rate to tax commodity exporters (who may belong to a different ethnic group) and then hand out cheap foreign exchange to ethnic supporters.

and low M2 to GDP ratios. and Easterly 1999a. people of Indian origin in Kenya). multiple ethnic groups might have conflicting interests on the kind of public services delivered by the state. and then hand out cheap loans to ethnic supporters. This kind of story applies to many ethnically diverse countries in Africa. where the commodity exports are concentrated in one ethnic group (e. as argued by Alesina. For example. a coalition of the smaller African ethnic groups in Kenya).g. Thus. I examine whether sound institutions mitigate the negative effects of ethnic fragmentation on policy choices by including the term INSTITUTIONS*ETHNIC in the regressions for policy indicators from Easterly and Levine 1997. flight of capital from the banking system. but they value schooling less because they cannot be taught in the language spoken at home. Ashantis in Ghana). and thus wind up investing less in such networks -leading to lower telephone density. They might reach a compromise lingua franca like Swahili. coastal ethnic groups in Ghana. and thus lower schooling. This would lead to less resources devoted to the common good. The result would be a negative real interest rate for depositors.g. and politicians belong to yet another group (e.11 rates to tax savers. which King and Levine 1993 find to be bad for growth. A pro-business set of institutions would prohibit such implicit expropriation of exporters and savers. linguistically distinct groups would have different preferences for the language of instruction in the schools. savings in another group (e. Alternatively. Good institutions like an independent and efficient bureaucracy may be able to supercede such differences and act for the good of the nation as a whole. I regress
. Baqir.g. Regionally separated groups might have trouble agreeing on the location of telephone networks.

political stability.so achieving a consensus for changing institutional rules of the game may be even more difficult in an ethnically diverse country.33) -. I also conduct the analysis instrumenting for my interaction term INSTITUTIONS*ETHNIC. Institutional arrangements can overcome the negative implications of ethnic diversity. exchange rate policies [see North. The coefficient magnitudes imply that the derivative of policies with respect to ETHNIC actually changes sign at very high values of institutions. Although this suggests a reform strategy that focuses on improving a country’s institutions. 8 There may also be reverse causation from policies to institutions. Hence. financial depth. Moreover. a black market premium creates incentives for corruption in foreign exchange allocation.12 measures of educational attainment. the results indicate that in countries with very highly developed institutions. which could affect my measure of institutional quality. In fact. For example. For educational attainment.
. the fiscal surplus. and the number of telephones per worker. the black market exchange rate premium. for example. INSTITUTIONS is itself negatively correlated with ETHNIC (simple correlation of –. the black market exchange rate premium (Figure 1). altering institutional arrangements is fundamentally more difficult than changing. 1990] and World Bank [1995]]. and the number of telephones per worker on ETHNIC and the interaction term INSTITUTIONS*ETHNIC. ethnic diversity does not significantly hurt policy choices. I find in OLS regressions that (1) ethnic diversity causes a deterioration in the dependent variable (consistent with the results of Easterly and Levine 1997) and (2) institutions significantly mitigate the negative effects of ethnic diversity (Table II). financial depth.

the form of Mauro’s variable (dummy variables for former French colonies. I find that sound institutions eliminate the negative effects of ethnic diversity on economic policies. Portugal. Spain. I normalize time since independence as the fraction of time since 1776 a country has been independent. a bigger black market exchange rate premium. etc. however. A more plausible instrument for my purposes is the length of time the country has been independent. 9 However. so there is no effect for INSTITUTIONS to mitigate. Furthermore. as in Mauro [1995].13 I could follow Mauro [1995] in the idea of using colonial heritage as an instrument. I also use the product of ethnic diversity and initial income (ETHNIC*INCOME) as an instrument. 10 This accords with the result by Easterly and Levine 1997 that ethnic diversity does not affect the fiscal surplus or the number of assassinations. Like Easterly and Levine 1997. when I do include the less than ideal instruments of colonial dummies for England.policies. less financial depth. as of the initial year of the decade for each decade observation. National colonial traditions seem to be correlated with the choice of policies (former French colonies in Africa in the Franc Zone do not have black market premia. and less infrastructure. for example).) is not suitable for this purpose since I need to find instruments uncorrelated with my dependent variables -. I find that ethnic diversity causes lower schooling. I also tried instruments to account for
. France. assuming that institutional development is a function of general economic development as represented by income. which could be interpreted as the length of time national institutions have had to develop. For these effects.. former English colonies. the results remain unchanged. The results (Table II) show no effect of ETHNIC and ETHNIC*INSTITUTIONS on the fiscal surplus and on the number of assassinations. etc.

and ethnic diversity
. and that INSTITUTIONS still mitigate this effect. 11 I fail to reject the over-identifying restrictions. Perhaps societies with good institutions are simply less prone to bad policy choices. population size.1999] natural resource abundance measures. The results on the black market premium are not robust to the inclusion of INSTITUTIONS separately. I find that ethnic diversity still causes lower schooling. When I use only the years since independence variable. an assumption which seems more well grounded for the years-since-independence variable than the income variable. I find no evidence that these instruments belong in the regression for policies directly. The results were still unchanged. as the regression cannot distinguish the effects of ETHNIC. Of course. War. and lower financial development. the pattern of signs and significance is unchanged (although coefficient magnitudes do shift). I did a Hausman test of the over-identifying restrictions to see if ETHNIC*INCOME and “years since independence” are indeed excludable from these policy regressions. regardless of their level of ethnic diversity. III. income. the use of instrumental variables technique addresses causality only if the instruments are truly exogenous. INSTITUTIONS. or their interaction. and land area. or this variable combined with an interaction term (yearssince-independence times ETHNIC). lower telephone density.14 natural endowments. This is helpful since it tells us that institutions is not simply proxying for. such as Sachs and Warner’s [1995. say. that is. I check whether this interaction term is really proxying for a direct effect of INSTITUTIONS on policy choices. institutions.

with peak civil war duration at ETHNIC=43. The last lines of Table II confirm that ethnic fractionalization increases the likelihood of war casualties. It is obvious from experience ranging from Afghanistan to Sudan that ethnic conflict sometimes takes on this most violent of forms. it is interesting to see if good institutions that mitigate economic consequences of diversity can modify violent ethnic conflict as well. Hence. once again good institutions are effective in mitigating this threat. Collier and Hoeffler 1998 find that the relationship between duration of civil war and ethnic diversity is quadratic. However. they do note that ethnic fractionalization is correlated with war casualties on national territory (data from Sivard 1993). The differing results from Collier and Hoeffler 1998 may be explained by my use of a different measure of intensity of civil war (casualties per capita rather than duration) and the inclusion of the institutional interaction effect. the effect of ethnic fractionalization on war is cancelled out all together. I tested a quadratic term for ETHNIC in my civil war regression.
.15 Although war is not the main theme of Easterly and Levine 1997 and is not the principal channel by which diversity affects growth. The interaction term between ETHNIC and INSTITUTIONS continued to be significantly negative. but found both ETHNIC and ETHNIC^2 to be insignificant in this case. This accords well with casual observation – ethnic differences may lead to civil war in Kosovo. and Sudan. Indeed at maximum quality institutions (INSTITUTIONS=10). or Switzerland. Canada. Rwanda. but they do not in Belgium.

the French in Sicily in 1282. the French in Bruges in 1302.16 I also tested whether INSTITUTIONS enters directly into the war casualties equation. Nestorian. execution. Greeks in Smyrna in 1922. Jews and Poles in the Ukraine in 1648-54. the French in Haiti in 1804. converted Jews in Portugal in 1507. The regression was not able to distinguish the separate effects of ETHNIC. the Flemings in England in 1381. institutions. and Maronite Christians in the Turkish empire in 1915-16. the Jewish Holocaust in German-occupied territory 1933-1945. Arab Christians in Lebanon in 1841. A non-exclusive list of victims of ethnic massacres over the last millenium includes: the Danes in Anglo-Saxon England in 1002. Serbians in Croatia in 1941. Haitians in the Dominican Republic in 1936. INSTITUTIONS.” The tragic history of genocide is a long one. 12
. Australia. and/or implied consent of sustained policies by governing elites or their agents – or in the case of civil war either of the contending authorities – that result in the deaths of a substantial portion of a communal and/or politicized communal group. and their interaction. defined as statesponsored killings whose victims are identified at least in part by their ethnic classification. According to Harff and Gurr 1996 “Geno/politicide is the promotion. the Jews in Europe during the First Crusade 1096-99. and Muslims and Hindus in British India in 1946-47. the Huguenots in France in 1572. indigenous populations in the US. and ethnic diversity Another violent manifestation of ethnic conflict is genocide. Turkish Armenians in 1895-96 and 1915-1916. Genocide. Jacobite. Jews in Russia in the 19th century. the Jews in Iberia in 1391. Protestants in Magdeburg in 1631. IV. and Tasmania in the 18th and 19th centuries.

Guatemala. Burma-Myanmar. Malaysia. Ethiopia. This group includes genocides in Angola. Countries in the lowest third of institutional quality have an increasing probability of genocide as ethnic fragmentation increases.5 in countries that are in the highest third of ethnic fragmentation and the lowest third of institutional quality. Guatemala. Figure 2 illustrates this result. The 16 countries are Angola. Uganda. Rwanda. Table IV shows the results. and Thailand. regardless of their level of ethnic diversity. Uganda. and Zaire. and Zaire-Congo. There are 16 countries that had a genocide over this period according to Harff and Gurr’s classification. Pakistan. Higher quality institutions make a given degree of ethnic diversity less likely to result in genocide. Pakistan. Sudan. Nigeria. Equatorial Guinea. Burundi. Nigeria. The measure they use (and I use here) is taken from Harff and Gurr 1996. Regression [1] shows the basic result: ethnic fragmentation has a significant and positive effect on the probability of genocide. Kampuchea-Cambodia. Sudan. Most striking of all. Here I use this data to construct a dummy variable that takes on the value 1 if a genocide (defined to include either “communal victims” or “mixed communal and political victims” in Harff and Gurr’s terminology) occurred at any time from 1960 to 1990. Conversely. Table III lists the dates and ethnic victims of the genocidal killings for these 16 countries. while the interaction term between ethnic fragmentation and INSTITUTIONS has a negative effect. Paraguay. countries in the upper third of institutional quality have NO genocides.17 Easterly and Levine 1997 noted that their measure of ethnolinguistic fragmentation was significant and positive in a probit equation for the occurrence of genocide. Here I investigate whether the presence of high quality institutions lowers the probability of genocide for a given amount of ethnolinguistic fragmentation.
. Somalia. countries in the upper two-thirds of institutional quality do not show an increasing probability of genocide as ethnic fragmentation increases. Examples of countries with high ethnic fragmentation but also high quality institutions include Canada. The probability is all the way up to . Indonesia.

the regression has trouble distinguishing among ETHNIC. It may be that the INSTITUTIONS variable is a proxy for more general legal safeguards for ethnic minorities. Economists should do more case studies of successful and unsuccessful examples of ethnic groups
. Good institutions also lower the risk of wars and genocides that might otherwise result from ethnic fractionalization. The price that this nation must pay for the continued oppression and exploitation of the Negro or any other minority group is the price of its own destruction. using the well-known Gastil index for suppression of democratic rights. these seems to be more important than political freedoms in mitigating the effect of ethnic diversity on the likelihood of genocide. while the institutional quality interaction effect remains significant. 13 V. Conversely.18 In regression [2]. as they affect whether ethnic conflict is destructive or is contained by the rules of the game. If we take institutional quality as a measure of economic and legal freedoms. INSTITUTIONS. In regression [3]. I find that institutional factors interact with ethnic diversity. --Martin Luther King Jr. poor institutions have an even more adverse effect on growth and policy when ethnic diversity is high. The interaction with democracy is insignificant. Mauro 1995) have found strong institutional effects of corruption and lack of rule of law on economic growth. This is a promising area for future research. Easterly and Levine 1997 found direct and indirect effects of ethnic diversity on economic growth. To put it another way. and their interaction. I examine whether INSTITUTIONS enters the probit equation for genocide directly. As with some of my other results. Ethnic diversity has a more adverse effect on economic policy and growth when institutions are poor. ethnic diversity does not lower growth or worsen economic policies. I test whether institutional quality is simply proxying for democracy. Conclusions Previous studies (Knack and Keefer 1995. in countries with sufficiently good institutions. Ethnically diverse nations that wish to endure in peace and prosperity must build good institutions.

19 co-existing within nations. What can we learn from the abundant historical data about the possible economic or social determinants of ethnic war and genocide? What more can governments do to finally bring the sad history of ethnic conflicts to an end?
. The study of oppression of one ethnic group by another is a rich area for further investigation – what conditions facilitate or prevent oppression? How much does the answer depend on initial inequality between ethnic groups? How much does the answer depend on the definition of ethnicity? The study of ethnically-based war and genocide is also a fruitful area for further research.

7
Collier has a related result.
I also failed to find any effect on the other 8 measures of political instability mentioned in Easterly
and Levine.
2 3
This analysis by social scientists represents a long tradition. p. 617. The BERI index is made up of measures of (1)Bureaucratic Delay. with the exception of constitutional changes. p. Greenberg (1980) who
notes the “continuing reality of racial and ethnic domination.
5
6. that democracy eliminates the adverse effect of ethnic fragmentation on
growth.
9.
12
Bell-Fialkoff 1996. I form residuals from the two stage least regression. where N is the number of observations.
(3)Nationalization Risk. YRSINDEP).stanford. The test statistic is distributed χ2 with one degree of freedom (two excluded exogenous variables minus one endogenous variable). p. INCOME*ETHNIC. 10-11 p.5)
4
Psacharopoulos and Patrinos 1994. p. then
regress them on all of the exogenous variables (ETHNIC.31
Endnotes
1
Bell-Fialkoff 1996. which matches their results. 6
This is similar to the formula proposed by Rodrik 1999 for response to shocks.” (p. (2) Contract Enforceability.
11. and (4) Infrastructure Quality. A similar idea is Barro’s [1997] use of (Spanish) colonial heritage as an instrument for inflation.
8
Mauro 1995 earlier noted an association between ethnolinguistic fractionalization and corruption.
See the description in Greene. The test statistic is equal to N times the R2 of the second regression.g.edu/group/King/speeches/Speech_at_the_great_march_on_detroit.
10.html
13
. Adelman and Morris 1967. 10-11 From http://www. 41. See e.